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Internal linking is one of those search engine optimization (SEO) topics that sounds simple until you actually try to improve it.

I have over 200 blog posts on this website. I know internal linking matters. And I still cannot find a tool that tells me what I actually need to know: which specific web page should link to which other web page, where the link belongs, and why it makes sense.

So I tried to build one myself.

That experience made the gap in existing tools much clearer.

What most internal linking tools do well

Many tools are good at the auditing side of internal linking.

They can usually tell you things like:

1. How many internal links exist on a web page or across a website.
2. Whether a web page appears to be orphaned.
3. Whether anchor text is repetitive, vague, or overly generic.
4. Whether navigation and contextual linking appear healthy at a high level.
5. Whether there are broad internal linking patterns worth reviewing.

That kind of reporting has value. It gives a quick snapshot, helps identify obvious problems, and creates a starting point for discussion.

But that is also where many tools stop.

Where many internal linking tools fall short

Most website owners do not need another dashboard telling them they have a score of 82 out of 100 or that they should improve their navigation structure. They need help making decisions.

That means answering questions such as:

1. Which specific web page should link to which other web page?
2. Why is that link relevant?
3. Where on the web page should the link be placed?
4. What anchor text would make sense in context?
5. Which suggested links matter most if time is limited?

This is where many tools start to break down. They are good at summarizing the condition of a website. They are much weaker at bridging the gap between diagnosis and action.

Why I tried to build this myself

After running into the same wall with existing tools, I started exploring whether I could build a solution using AI-assisted development. The idea was straightforward: take my blog post data, generate embeddings to represent topical relationships between posts, and surface specific web page-to-web page linking recommendations based on semantic similarity.

In practice, it turned out to be significantly harder than it sounds. Getting the data organized was one challenge. Building the logic to translate similarity scores into actionable recommendations, with context about where on the web page a link belongs and what anchor text would fit, was another level entirely.

The technical pieces exist. Connecting them into something genuinely useful for a working website owner is where things break down fast.

That experience gave me a clearer picture of why existing tools stop where they do. The auditing side is relatively tractable. The decision-support side requires understanding content at a level that is much harder to automate well.

The problem with surface-level internal linking metrics

Some internal linking metrics are directionally useful. They can point to potential issues. But many become less helpful when they are presented as definitive measures of quality.

Take link counts, for example. A high number of internal links on a web page does not automatically mean the web page is well linked. Those links might be mostly navigation, footer, archive, or template links. They may not help a user discover the next best piece of content or help search engines understand topical relationships in any meaningful way.

Orphan web page detection can be genuinely useful. But even here, the insight is limited unless the tool helps answer the next question: which existing web page should link to that orphaned web page, and why?

Anchor text scoring has similar limitations. It is easy to say anchor text should be descriptive. That is true. But a real tool should go further and help identify what descriptive anchor text makes sense inside the actual sentence and context of the referring web page.

Even navigation-related recommendations can drift into generic advice. Suggestions like “improve website structure,” “add breadcrumbs,” or “add a search bar” may sound strategic, but they often do little to solve the specific editorial linking decisions that content-heavy websites struggle with most.

Why website owners need more than an audit

A website owner usually is not asking, “How many internal links do I have?”

The real questions are closer to these:

1. Which web pages on my website are under-supported?
2. Which existing web pages are the best candidates to support them?
3. How do I add links in a way that feels natural and helpful?
4. Which opportunities are worth acting on first?

That is a different problem than auditing. It is a recommendation problem. It is a prioritization problem. It is also a context problem.

Without context, internal linking advice stays abstract. With context, it becomes usable.

What a truly helpful internal linking system should do

If internal linking tools are going to become genuinely useful for website owners, they need to move beyond scoring and into decision support.

A more helpful internal linking system would do at least five things well.

1. Identify the right source and destination web pages. It should not just say a web page needs more links. It should show which existing web pages are the strongest candidates to link to it.
2. Explain why the recommendation exists. There should be a clear rationale, such as shared topic coverage, overlapping keyword intent, supporting subtopic relationships, or complementary user journeys.
3. Suggest where the link belongs. A recommendation is far more useful when it points to a specific paragraph, heading, or section where the link would fit naturally.
4. Offer anchor text guidance grounded in the web page content. Not generic anchor text rules. Actual suggestions that fit the language already on the web page.
5. Prioritize recommendations based on likely impact. Not every link opportunity matters equally. A good system should help website owners understand which fixes are high value, which are nice to have, and which can wait.

The difference between auditing and decision-making

This is the core distinction that many tools miss.

Auditing tells you what exists. Decision-making tells you what to do next.

Auditing can tell you that a website has strong internal link density, no orphaned web pages, and descriptive anchor text across most web pages.

Decision-making tells you that a post about misleading data visualizations should probably link to a related post about poor chart design, and that the best placement is in the paragraph that introduces the risks of decontextualized reporting.

One is a score. The other is useful.

This is not just an SEO problem

Internal linking is not only about search performance.

Good internal linking improves website usability, increases content discovery, supports stronger journeys across a website, and helps people move from awareness to trust to action. It can keep visitors engaged longer, connect isolated insights, and surface relevant resources they would not otherwise find.

That is why surface-level scoring is not enough. Internal linking is part SEO, part information architecture, and part editorial judgment. Any tool that ignores those realities will only solve part of the problem.

What to look for in an internal linking tool

If you are evaluating internal linking tools, it helps to ask better questions than whether the dashboard looks polished or the score seems high.

Questions worth asking include:

1. Does this tool help me make web page-to-web page linking decisions?
2. Does it explain why a recommendation makes sense?
3. Does it help me place the link in context?
4. Does it distinguish between template links and meaningful contextual links?
5. Does it save me real time, or just give me another report to interpret?

A tool that cannot answer those questions well may still be useful for orientation, but it is probably not solving the real internal linking problem.

The bigger opportunity

The future of internal linking tools should not be more colorful scorecards or more generic advice. It should be better judgment support.

I have not found a tool that does this well yet. I am still looking, and still experimenting with building something myself, though that has proven harder than expected. What I do know is that the gap is real and the need is not complicated to describe: website owners need help moving from “I know I should improve internal linking” to “here is exactly what to change and why.”

Until more tools bridge that gap, internal linking will remain one of those areas where the theory is easy, the dashboards look impressive, and the real work still falls back on the website owner.

I am still waiting for the tool that changes that. If you have found one, I would genuinely like to know.

Image alt text still matters. Writing it manually does not.

If your website has dozens or hundreds of images, opening each one individually in the Media Library is not a realistic workflow. A better approach is to export the image records you need, use AI to generate baseline alt text in bulk, review the output, and update the records back into WordPress.

This walkthrough focuses on WordPress, but the core workflow applies more broadly to any content management system that allows export, bulk processing, and structured updates. The exact tools may vary, but the process stays the same: export the right fields, generate alt text in bulk, review the results, and apply the updates cleanly.

Why image alt text still matters

Alt text serves two practical purposes.

1. Accessibility. Screen readers rely on alt text to describe images to users who cannot see them.
2. Image context. Search engines use image-related signals such as file names, surrounding content, and alt text to better understand what an image represents.

Alt text is not a magic search engine optimization lever by itself, but missing alt text at scale is still a quality gap worth fixing.

Why you should not be doing this manually

Most website owners and marketers do not have an alt text problem. They have a workflow problem.

The old method is to open each image, write alt text one at a time, save it, and repeat until you lose momentum. That might work for a small batch, but it does not scale when a website has years of accumulated content.

The better goal is baseline coverage at scale.

That means using AI to get from zero to good enough, then manually refining only the images that matter most, such as featured images, charts, infographics, product images, and images on high-traffic web pages.

What image fields are worth caring about

If you are exporting image-related data, keep your focus narrow. Alt text is the main field worth solving first.

1. ID. This makes importing or matching updates much easier and safer.
2. Image URL or file path. This usually contains the file name, which often gives AI enough context to generate a usable baseline alt text value.
3. Alt Text. This is the field you want AI to fill or improve.
4. Title. Optional. This can be cleaned up later, but it is lower priority than alt text.
5. Caption. Optional. Only useful if captions actually appear on your web pages.
6. Description. Usually not worth the effort unless you have a specific reason to maintain it.

If you want the simplest, highest-return workflow, export ID, image URL, and Alt Text.

What to export from WordPress

You do not need a perfect media export to make this work. In many cases, exporting the image data tied to posts or web pages is enough to create a strong first pass.

Your export should include these columns:

1. ID
2. Post title or web page title if available
3. Image URL
4. Existing Alt Text
5. Optional fields such as Title or Caption if you want to address them later

The key requirement is simple. Your export needs to give AI enough information to infer what each image likely is, and enough structure for WordPress to match each record during the update process.

What AI is actually doing here

This method works because many website image files already contain useful context in the file name.

For example:

digital-marketing-roundup-2026-march.jpg

becomes:

Digital marketing roundup March 2026 infographic

That is not perfect human-crafted alt text, but it is far better than leaving the field blank, and it can be generated at scale quickly.

The challenge is not generating alt text. The challenge is structuring and applying it correctly.

The practical workflow

1. Export the image-related records from WordPress.
2. Make sure the file includes ID, Image URL, and Alt Text.
3. Upload the CSV or spreadsheet to an AI assistant.
4. Ask AI to generate concise, human-readable alt text for each row based on the image URL or file name.
5. Review the output and flag any vague or inaccurate entries.
6. Update the file back into WordPress using the most reliable method available in your setup.
7. Spot check a sample of records after the update to confirm the changes worked.

How to make this work in WordPress without paid import plugins

In practice, importing alt text back into WordPress is where most workflows break.

After testing multiple approaches, the most reliable method is to update image alt text directly using a simple one-time script.

Step 1: Restructure your data

Your file must have one image per row:

imageurl, alttext

Step 2: Upload your CSV file

Upload the file to your Media Library and copy the file URL.

Step 3: Run a one-time update script

add_action('admin_init', function() {
    if (!current_user_can('manage_options')) return;

    $csv_url = 'YOUR_CSV_FILE_URL_HERE';
    $response = wp_remote_get($csv_url);
    if (is_wp_error($response)) return;

    $csv = wp_remote_retrieve_body($response);
    if (!$csv) return;

    $lines = preg_split('/\r\n|\r|\n/', trim($csv));
    if (!$lines || count($lines) < 2) return;

    $rows = array_map(function($line) {
        return str_getcsv($line, ',', '"', '\\');
    }, $lines);

    array_shift($rows);

    foreach ($rows as $row) {
        if (!is_array($row) || count($row) < 2) continue;

        $image_url = trim($row[0]);
        $alt_text = trim($row[1]);

        if (!$image_url || !$alt_text) continue;

        $attachment_id = attachment_url_to_postid($image_url);

        if ($attachment_id) {
            update_post_meta($attachment_id, '_wp_attachment_image_alt', $alt_text);
        }
    }
});

After running this once, disable the script.

Where this breaks down and how to avoid it

This is where you can lose hours if you get it wrong.

1. Multiple images in a single row
   Fix: Ensure one image URL per row.
2. Truncated image URLs
   Fix: Verify full paths are intact.
3. Import tools blocking custom fields
   Fix: Update directly via _wp_attachment_image_alt.
4. Mismatch with WordPress structure
   Fix: Match using image URL to attachment ID.
5. Over-optimizing low-impact fields
   Fix: Focus on alt text first.
6. Trying to fix everything at once
   Fix: Prioritize high-impact images.

Final takeaway

Image alt text is still worth having, but the solution should be more automated than manual.

Export the data, generate a baseline with AI, apply updates cleanly, and move on.

Better coverage, less friction, and a workflow you can actually repeat.